ChemBL
Chemical Biology DatabaseComprehensive database of bioactive molecules, providing information on their biological activities, targets, and medicinal chemistry properties. It serves as a valuable resource for drug discovery and dev't, allowing researchers to explore and analyze chemical structures, pharmacological data, and molecular interactions.
PubChem
Public Chemical DatabaseFreely accessible database that houses information on the biological activities of small molecules. It comprises chemical structures, properties, biological assays, and associated data. PubChem plays a crucial role in facilitating chemical research, enabling scientists to explore the vast landscape of small molecules and their potential app's.
PDB
Protein Data BankWorldwide repository of experimentally determined three-dimensional structures of biological macromolecules, primarily proteins and nucleic acids. PDB provides researchers with access to an extensive collection of structural data, enabling the analysis of protein folding, ligand binding, and molecular interactions.
Data Collection
from ChEMBL databaseGathering large amounts of genetic and molecular data
- Data Collection
- Gather Data
- ChEMBL Database
- Ready for Analysis
Data Analysis
to Preprocess and PreparationBy various statistical and computational tools
- Data Analysis
- Interpret the data
- Preprocess & Prepare
- Ready for Build Model
Build Model
with Regression modelBuild predictive models that can identify potential drug
- Build Model
- Regression Model
- Model Comparasion
- Ready for Deployment
Deployment
with StreamlitDeveloped AI models available for practical use
- Deployment
- Use Streamlit
- HTML, CSS & JS
- Host on GitHub
Safe & high-speed Discovery
Process of developing new medications and therapies for the treatment of breast cancer using artificial intelligence techniques.
AI algorithms are used to identify and analyze vast amounts of data related to the disease, such as genetic mutations, tumor characteristics, and patient data, to develop new drugs and treatment options that can be personalized to the individual patient.
By leveraging the power of AI, drug discovery for breast cancer can be done faster and more efficiently, potentially leading to more effective treatments and better outcomes for patients.
AI can also help identify patient subgroups that may respond better to certain treatments, leading to personalized medicine and better outcomes for breast cancer patients. Overall, AI has the potential to revolutionize the field of drug discovery for breast cancer and improve patient outcomes.
What can you expect?
-
Up-to-date Information
Find up-to-date information on the latest advances in AI technologies being used to develop new drugs and treatments for breast cancer.
-
Used for Resources and Tools
Provide access to resources and tools for researchers, clinicians, and patients, such as data sets, machine learning algorithms, and predictive modeling software.
-
Collaboration and Knowledge Sharing
Can serve as a platform for collaboration and knowledge-sharing among experts in the field, including researchers, pharmaceutical companies, and patient advocacy groups.